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Deterministic Diagnostic Pattern Generation (DDPG) for Compound Defects

机译:用于复合缺陷的确定性诊断模式生成(DDPG)

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Scan chain failure diagnosis has become an important means for silicon debug and yield improvement. Although plenty of prior work discussed how to perform scan chain diagnosis, most of the previously proposed techniques made an assumption that the system logic is fault-free, which could be an impractical assumption leading to incorrect diagnostic results. In this paper, we propose a scan chain Deterministic Diagnostic Pattern Generation (DDPG) method that can tolerate the faults in the system logic without degradation of chain diagnostic resolution and precision. The entire flow includes three steps. In the first step, patterns are created to propagate the state of a targeted scan cell to as many reliable observation points as possible. In the second step, the load error probability of each targeted scan cell is calculated based on the Hamming Distances between the observed responses and the expected good or faulty responses. In the last step, a suspect profile is plotted, which can be used to identify the suspect scan cell(s) based on ranking scores. Experimental results show that the diagnostic resolution and precision are not degraded even with dozens of faults injected into the system logic.
机译:扫描链故障诊断已成为硅调试和产量改进的重要手段。尽管讨论了大量的事先工作如何执行扫描链诊断,但大多数先前提出的技术都假设系统逻辑无故障,这可能是一种不切实际的假设,导致不正确的诊断结果。在本文中,我们提出了一种扫描链确定性诊断模式生成(DDPG)方法,可以容忍系统逻辑中的故障,而不会降低链诊断分辨率和精度。整个流程包括三个步骤。在第一步中,创建模式以将目标扫描单元的状态传播到尽可能多的可靠观察点。在第二步中,基于观察到的响应和预期的良好或故障响应之间的汉明距离来计算每个目标扫描单元的负载误差概率。在最后一步中,绘制了可疑的配置文件,其可用于识别基于排名分数的可疑扫描单元。实验结果表明,即使在系统逻辑中注入数十个故障,诊断分辨率和精度也不会降低。

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